As edge cloud computing, AI/ML, and IoT revolutionize computing, many enterprises are considering pulling back on data center operations in favor of cloud-based solutions. The reasons to consider alternatives to on-prem data centers are valid: They can be expensive to operate, and it’s increasingly difficult to recruit and retain staff with the right skills. Moreover, the concept of a physical data center can feel unnecessary in the new, highly distributed world, where users, applications, and data need to be everywhere.
Many enterprises have responded by outsourcing network and data center management to service providers. But is that the right solution for every business?
Cloud economics are complex, and the ways that providers charge – especially when based around typical and peak application use – can be challenging and ill-suited for some organizations. Some tasks are less expensive to do off-premises (either through a shared facility or the cloud), while others may end up costing more. Data security and privacy concerns may also factor into the equation.
Many productivity applications are moving to the cloud as a cost-saving measure, but there are different factors in play with business-built applications meant to serve customers and for certain mission-critical applications. Even if moving to the cloud may save on cost, it can limit an organization’s control over the user experience of its customers and its strategic assets. Of course, edge computing, IoT, and cloud computing require businesses to start rethinking the architecture of the data center. But whether data and applications are housed in a company’s data center or a provider’s data center, the need for control and remediation doesn’t go away.
This need for specialization and control means that in-house data centers are too important a part of the IT operation to abandon entirely, and as such will likely remain an important part of the overall IT strategy for the foreseeable future. For most enterprises, digital transformation is a long evolution that is best served with a blended approach that combines a phased migration of applications and data to the cloud with a mix of legacy and cloud-native services.
The Challenges of Managing a Modern Data Center
Regardless of architecture, the challenges data centers face today – from finding people with the right skills to keeping a lid on costs to reliably managing ever-increasing amounts of data without issues – are likely to persist.
A key factor in these challenges is the way that data center networks have evolved over the years with increasingly specialized subsystems and devices. Historically, operations teams had to know the syntax for each one and spend time manually interacting with each device. More recently, the library of specialized automation and individualized scripts to try and improve the situation has become their own complex patchwork of upkeep and effort.
Additionally, each subset and vendor has dedicated management with their own set of dashboards, monitors, and alerts. All of these are designed to help data center technicians diagnose and resolve problems, but the reality is that there’s simply too much to manage. The increased complexity inherent to modern data centers threatens network reliability and slows down the speed of change.
Improving Day 2 Operations
With the rise of complex, automated solutions for common processes, the focus of data center staff has shifted to optimizing Day 2 operations.
The overall goal is to operate the network as a single system. That means first taking a unified, intent-based approach to design. Second, it means implementing open networking principles and multi-vendor support that reflect the diversity of data center environments and the reality of their existing investments.
The network that the design team intended on Day 0, and the engineering team deployed on Day 1, should be the same one that the operations team runs on Day 2. The combination of automated closed-loop and intent-based analytics eliminates common day-to-day pitfalls of manual infrastructure management as well as lengthy and frustrating troubleshooting hunts. Managing the network cohesively enables operations teams to do their jobs more effectively and frees them up to focus on more rewarding, productive work.
By taking a holistic view of automation, the Day 2 operations team can also ensure that what the architects originally intended doesn’t get lost in translation as needs change and the network evolves.
Incorporating automation into Day 2 operations also benefits organizational agility. Imagine a business is launching a new service that has been months in the making. On the day of go-live, a fault develops, and multiple virtual machines misconfigured with duplicate MAC addresses cause intermittent reachability issues, breaking not only the new application but others as well. How long would that take to find and fix with manual tools alone? Days or longer? Adopting automated validation steps ahead of time ensures that such misconfigurations don’t happen, and the new service launches smoothly and on schedule.
That’s not to say operational problems will never happen. But when they do, automated Day 2 operations simplify the process of finding the needle in the haystack for fast time to resolution. Automation can also help avert outages with predictive insights and change control to minimize the impact of human error.
The data center is evolving but there’s no question that it’s here to stay. Automating data center operations all the way through Day 2 can have a dramatic impact on the time and uptime of running a data center. By reducing complexity, improving response times, and minimizing the risks of delays and interruption to business, data center automation lets teams win in their own race to transformation.